Software process improvement using an electronic process guide

Kasvava kiinnostus ohjelmistojen laatua kohtaan on herättänyt ohjelmistoprosesseihin ja niiden kehittämiseen kohdistuvaa huomiota viime vuosina. Ohjelmistoyritykset ympäri maailmaa ovat ottaneet käyttöön ohjelmistoprosessin kehittämismalleja, kuten CMM ja SPICE, pyrkiessään kohti parempilaatuisia ohjelmistotuotteita. Samalla on huomattu, että tehokas prosessien parantaminen ja suorittaminen tarvitsee tuekseen kuvauksen prosessista, jotta prosessin perusteellinen ymmärtäminen ja kommunikointi olisi mahdollista. Ohjelmistoprosesseja voidaan kuvata monilla eri tavoilla. Prosessiopas on prosessin esitysmuoto, jonka päätarkoituksena on helpottaa prosessin ymmärtämistä ja kommunikointia. Elektroninen prosessiopas on Web-teknologiaa hyödyntävä prosessiopas. Tässä työssä luodaan kehitysympäristö elektronisille prosessioppaille, joiden tarkoituksena on tukea ohjelmistoprosessin kehittämistä ja suorittamista. Ympäristö mahdollistaa ohjelmistoprosessinmallintamisen sekä yksilöllisten oppaiden luomisen ja muokkaamisen. Kehitysympäristöä käytetään mallintamaan tietoliikenneohjelmistoja valmistavan yrityksen ohjelmistoprosessia sekä luomaan elektronisia prosessioppaita tukemaan prosessin kehitystä ja suorittamista. Lopuksi pohditaan prosessioppaiden tarjoamaa tukea sekä mahdollisuuksia kohdeyrityksessä.

Electronic publishing : guide to selection /

Mode of access: Internet.

MyPersonal-EPG: um EPG personalizável e com suportes a recomendações para o SBTVD

In this work we present the architecture and implementation of MyPersonal-EPG, a personal EPG with support to recommendations, built on top of the Ginga middleware, that fulfill the following requirements: (i) to allow users to build their own personal programming grids, based on programming guides from several broadcasters; (ii) to offer a mechanism to tune the desired channels on the moment the selected programs are about to begin; (iii) to allow users to select the desired programs categories; (iv) to offer programs recommendations, in both synchronous and asynchronous way, based on the categories previously selected by users; (v) to allow users to modify the current configuration options; (vi) to allow the creation of several users accounts, so that each user can store its own information. The application‟s usability test is also presented and its results are discussed and analyzed

Solução doméstica para televisão digital

Mestrado em Engenharia Electrotécnica e de Computadores

Media Brokerage: Agent-Based SLA Negotiation

Media content personalisation is a major challenge involving viewers as well as media content producer and distributor businesses. The goal is to provide viewers with media items aligned with their interests. Producers and distributors engage in item negotiations to establish the corresponding service level agreements (SLA). In order to address automated partner lookup and item SLA negotiation, this paper proposes the MultiMedia Brokerage (MMB) platform, which is a multiagent system that negotiates SLA regarding media items on behalf of media content producer and distributor businesses. The MMB platform is structured in four service layers: interface, agreement management, business modelling and market. In this context, there are: (i) brokerage SLA (bSLA), which are established between individual businesses and the platform regarding the provision of brokerage services; and (ii) item SLA (iSLA), which are established between producer and distributor businesses about the provision of media items. In particular, this paper describes the negotiation, establishment and enforcement of bSLA and iSLA, which occurs at the agreement and negotiation layers, respectively. The platform adopts a pay-per-use business model where the bSLA define the general conditions that apply to the related iSLA. To illustrate this process, we present a case study describing the negotiation of a bSLA instance and several related iSLA instances. The latter correspond to the negotiation of the Electronic Program Guide (EPG) for a specific end viewer.

Brokerage Platform for Media Content Recommendation

Near real time media content personalisation is nowadays a major challenge involving media content sources, distributors and viewers. This paper describes an approach to seamless recommendation, negotiation and transaction of personalised media content. It adopts an integrated view of the problem by proposing, on the business-to-business (B2B) side, a brokerage platform to negotiate the media items on behalf of the media content distributors and sources, providing viewers, on the business-to-consumer (B2C) side, with a personalised electronic programme guide (EPG) containing the set of recommended items after negotiation. In this setup, when a viewer connects, the distributor looks up and invites sources to negotiate the contents of the viewer personal EPG. The proposed multi-agent brokerage platform is structured in four layers, modelling the registration, service agreement, partner lookup, invitation as well as item recommendation, negotiation and transaction stages of the B2B processes. The recommendation service is a rule-based switch hybrid filter, including six collaborative and two content-based filters. The rule-based system selects, at runtime, the filter(s) to apply as well as the final set of recommendations to present. The filter selection is based on the data available, ranging from the history of items watched to the ratings and/or tags assigned to the items by the viewer. Additionally, this module implements (i) a novel item stereotype to represent newly arrived items, (ii) a standard user stereotype for new users, (iii) a novel passive user tag cloud stereotype for socially passive users, and (iv) a new content-based filter named the collinearity and proximity similarity (CPS). At the end of the paper, we present off-line results and a case study describing how the recommendation service works. The proposed system provides, to our knowledge, an excellent holistic solution to the problem of recommending multimedia contents.

A Multi–Agent Brokerage Platform for Media Content Recommendation

Near real time media content personalisation is nowadays a major challenge involving media content sources, distributors and viewers. This paper describes an approach to seamless recommendation, negotiation and transaction of personalised media content. It adopts an integrated view of the problem by proposing, on the business-to-business (B2B) side, a brokerage platform to negotiate the media items on behalf of the media content distributors and sources, providing viewers, on the business-to-consumer (B2C) side, with a personalised electronic programme guide (EPG) containing the set of recommended items after negotiation. In this setup, when a viewer connects, the distributor looks up and invites sources to negotiate the contents of the viewer personal EPG. The proposed multi-agent brokerage platform is structured in four layers, modelling the registration, service agreement, partner lookup, invitation as well as item recommendation, negotiation and transaction stages of the B2B processes. The recommendation service is a rule-based switch hybrid filter, including six collaborative and two content-based filters. The rule-based system selects, at runtime, the filter(s) to apply as well as the final set of recommendations to present. The filter selection is based on the data available, ranging from the history of items watched to the ratings and/or tags assigned to the items by the viewer. Additionally, this module implements (i) a novel item stereotype to represent newly arrived items, (ii) a standard user stereotype for new users, (iii) a novel passive user tag cloud stereotype for socially passive users, and (iv) a new content-based filter named the collinearity and proximity similarity (CPS). At the end of the paper, we present off-line results and a case study describing how the recommendation service works. The proposed system provides, to our knowledge, an excellent holistic solution to the problem of recommending multimedia contents.

Trendtv : uma arquitetura para mudança automática de canais de TV baseada em redes sociais virtuais com graus de amizade e suporte a múltiplos dispositivos no cenário da TV digital brasileira

Due to the large amount of television content, which emerged from the Digital TV, viewers are facing a new challenge, how to find interesting content intuitively and efficiently. The Personalized Electronic Programming Guides (pEPG) arise as an answer to this complex challenge. We propose TrendTV a layered architecture that allows the formation of social networks among viewers of Interactive Digital TV based on online microblogging. Associated with a pEPG, this social network allows the viewer to perform content filtering on a particular subject from the indications made by other viewers of his network. Allowing the viewer to create his own indications for a particular content when it is displayed, or to analyze the importance of a particular program online, based on these indications. This allows any user to perform filtering on content and generate or exchange information with other users in a flexible and transparent way, using several different devices (TVs, Smartphones, Tablets or PCs). Moreover, this architecture defines a mechanism to perform the automatic exchange of channels based on the best program that is showing at the moment, suggesting new components to be added to the middleware of the Brazilian Digital TV System (Ginga). The result is a constructed and dynamic database containing the classification of several TV programs as well as an application to automatically switch to the best channel of the moment

Televisão digital móvel e portátil: estudo de caso da televisão japonesa NHK

Pós-graduação em Televisão Digital: Informação e Conhecimento - FAAC

Desenvolvimento de um aplicativo de guia de programação de canais de TV digital

Pós-graduação em Televisão Digital: Informação e Conhecimento - FAAC

U.S. and U.K. standards system : report of standards workshop /

"Electronic resource guide"--P. 36-40.

Contribution à l’élaboration d’un guide alimentaire béninois : approche par la programmation linéaire et validation sur le terrain

Contexte: Le Bénin est atteint par le double fardeau nutritionnel : dans le même pays, et parfois dans le même ménage, il y a des personnes malnutries et d’autres aux prises avec des maladies chroniques. Ces conditions, au moins pour partie, peuvent être prévenues si la population est sensibilisée à de bonnes habitudes alimentaires. Pour ce faire, les professionnels de la santé ont besoin d’outils comme un guide alimentaire (GA) pour faciliter l’apprentissage de bonnes pratiques alimentaires. Ce dernier nécessite plusieurs étapes à son élaboration, dont la définition des groupes alimentaires, la présentation visuelle et la quantification des portions d'aliments. Objectif : Ce travail a eu pour but de proposer et d’homologuer des portions quotidiennes d’aliments dans chaque groupe alimentaire pour différents groupes d’âge de Béninois. Méthode : Elle consiste à : 1) Caractériser la consommation alimentaire locale; 2) Optimiser le profil moyen de consommation alimentaire quotidienne à l’aide de la programmation linéaire (PL); 3) Traduire les résultats en termes de nombre et taille de portions d’aliments de chaque groupe à consommer quotidiennement; 4) Illustrer les recommandations au moyen d’exemples de menus journaliers; 5) Homologuer le prototype du GA avec des experts béninois. La PL a permis de déterminer les choix d’aliments et quantités optimales à recommander à partir des enquêtes transversales récentes et des recommandations nutritionnelles de l’OMS. Résultats : Les quantités et portions d'aliments recommandées à la consommation ont été déterminées. Les résultats ont été partagés avec les personnes-ressources en nutrition au Bénin. Le premier prototype du GA a été développé pour restitution subséquente aux autorités du Bénin.

Lagrangian-informed mixed integer programming reformulations

La programmation linéaire en nombres entiers est une approche robuste qui permet de résoudre rapidement de grandes instances de problèmes d'optimisation discrète. Toutefois, les problèmes gagnent constamment en complexité et imposent parfois de fortes limites sur le temps de calcul. Il devient alors nécessaire de développer des méthodes spécialisées afin de résoudre approximativement ces problèmes, tout en calculant des bornes sur leurs valeurs optimales afin de prouver la qualité des solutions obtenues. Nous proposons d'explorer une approche de reformulation en nombres entiers guidée par la relaxation lagrangienne. Après l'identification d'une forte relaxation lagrangienne, un processus systématique permet d'obtenir une seconde formulation en nombres entiers. Cette reformulation, plus compacte que celle de Dantzig et Wolfe, comporte exactement les mêmes solutions entières que la formulation initiale, mais en améliore la borne linéaire: elle devient égale à la borne lagrangienne. L'approche de reformulation permet d'unifier et de généraliser des formulations et des méthodes de borne connues. De plus, elle offre une manière simple d'obtenir des reformulations de moins grandes tailles en contrepartie de bornes plus faibles. Ces reformulations demeurent de grandes tailles. C'est pourquoi nous décrivons aussi des méthodes spécialisées pour en résoudre les relaxations linéaires. Finalement, nous appliquons l'approche de reformulation à deux problèmes de localisation. Cela nous mène à de nouvelles formulations pour ces problèmes; certaines sont de très grandes tailles, mais nos méthodes de résolution spécialisées les rendent pratiques.

JISC TechDis Accessibility essentials guide: Making electronic documents more readable

The TechDis Accessibility Essentials Guide for Reading has been divided into the following three sections: Font colours and styles; Enlarging text and Navigating documents. These guides have been designed to give practical step-by-step information to enable anyone reading electronic material to amend its look and feel into a style which suits them, their audience or the context in which it is used.

Computer model documentation guide /

Item 247.